基于柔顺机构的新型可变形机翼设计方法研究

机翼翼型变体技术可以根据任务和环境自适应地改变机翼形状、厚度、弯度等重要参数,使飞机在不同飞行状态下都能取得较理想的气动特性。柔顺机构是实现机翼蒙皮光滑变形的驱动装置,相比传统液压机构具备质量特性好的优势。采用鱼骨型柔性钢架与四连杆机构实现了机翼前缘上下蒙皮向内收缩、前缘形状由钝变尖的弹性变形过程。通过设计“撞块”机构实现驱动行程的有效分解,解决了前缘尖端开口处蒙皮回收与机翼变形控制所需的驱动行程不一致的内在矛盾。变形后翼型与目标翼型误差最大位置不超过4 mm,变形过程中结构最大应力小于材料许用应力值。相比传统采用纯液压机构驱动的变形机翼设计方案,该基于柔顺机构的变体机翼结构减质14.1%。     

Reliability analysis of arresting hook engaging arresting cable for carrier-based aircraft influenced by multifactors

The carrier-based aircraft landing and arrest process is complex and nonlinear, and includes the coupling effect between the aircraft and arresting system. It has many uncertain factors, which lead to difficulty in the reliability analysis. To make the reliability analysis more accurate and effective, this paper presents some studies. Taking a certain type of carrier-based aircraft as the research object, a dynamic model of the landing and arrest cable was established, and the accuracy of the model was verified using laboratory test results. Based on the model, this paper shows how the key parameters, including the sinking velocity, pitch angle and horizontal velocity, affect the collision rebound performance of the arresting hook. After that, a limit state equation of the arresting hook system’s reliability was established. For the implicit limit state equation, a surrogate model of the reliability of the arresting hook was established using the Support Vector Machine (SVM) method, and then reliability analysis was carried out using the Monte Carlo method. Finally, it was explained in detail how the key parameters affect the reliability of the hook engaging the arresting cable, and some meaningful conclusions were obtained. This analysis method and its results can provide a reference for the top-level parameter design of carrier-based aircraft and reliability research on the arresting systems.     

A robust Poisson multi-Bernoulli filter for multi-target tracking based on arithmetic average fusion

The coalescence and missed detection are two key challenges in Multi-Target Tracking (MTT). To balance the tracking accuracy and real-time performance, the existing Random Finite Set (RFS) based filters are generally difficult to handle the above problems simultaneously, such as the Track-Oriented marginal Multi-Bernoulli/Poisson (TOMB/P) and Measurement-Oriented marginal Multi-Bernoulli/Poisson (MOMB/P) filters. Based on the Arithmetic Average (AA) fusion rule, this paper proposes a novel fusion framework for the Poisson Multi-Bernoulli (PMB) filter, which integrates both the advantages of the TOMB/P filter in dealing with missed detection and the advantages of the MOMB/P filter in dealing with coalescence. In order to fuse the different PMB distributions, the Bernoulli components in different Multi-Bernoulli (MB) distributions are associated with each other by Kullback-Leibler Divergence (KLD) minimization. Moreover, an adaptive AA fusion rule is designed on the basis of the exponential fusion weights, which utilizes the TOMB/P and MOMB/P updates to solve these difficulties in MTT. Finally, by comparing with the TOMB/P and MOMB/P filters, the performance of the proposed filter in terms of accuracy and efficiency is demonstrated in three challenging scenarios.     

Adaptive cubature Kalman filter with the estimation of correlation between multiplicative noise and additive measurement noise

Mobile robots are often subject to multiplicative noise in the target tracking tasks, where the multiplicative measurement noise is correlated with additive measurement noise. In this paper,first, a correlation multiplicative measurement noise model is established. It is able to more accurately represent the measurement error caused by the distance sensor dependence state. Then, the estimated performance mismatch problem of Cubature Kalman Filter(CKF) under multiplicative noise is analyzed. An i...